| Course title | Data Analysis and Visualisation |
|---|---|
| Course code | KI/EDAV |
| Organizational form of instruction | Lecture + Lesson |
| Level of course | unspecified |
| Year of study | not specified |
| Semester | Winter and summer |
| Number of ECTS credits | 9 |
| Language of instruction | English |
| Status of course | unspecified |
| Form of instruction | Face-to-face |
| Work placements | This is not an internship |
| Recommended optional programme components | None |
| Course availability | The course is available to visiting students |
| Lecturer(s) |
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| Course content |
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1. Introduction to Matlab 2. Programming and plotting in Matlab 3. Matrices and matrix operation in Matlab 4. Function of one real variable, numerical differentiation and integration 5. Ordinary differential equations 6. Signal and image processing: filtering, transformation (Fourier, wavelets) 7. Introduction to R: data structures, writing functions, control statements, loops, data manipulation, plots etc. 8. Basic concepts of descriptive statistics: methods of data processing, frequency distribution (histogram, polygon) 9. The statistical analysis of univariate data: moment/quantile measures of central tendency, variability, skewness and kurtosis 10. Statistical analysis of multivariate data: correlation, factor and cluster analysis 11. Regression analysis: linear and nonlinear regression models 12. Analysis of time series: graphical analysis, decomposition, autocorrelation, trend modeling 13. Summary of selected techniques of static and dynamic visualization
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| Learning activities and teaching methods |
| unspecified |
| Learning outcomes |
| Prerequisites |
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unspecified
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| Assessment methods and criteria |
|
unspecified
basics of procedural programming (conditional statements, loops, procedures) elementary algebra and calculus |
| Recommended literature |
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| Study plans that include the course |
| Faculty | Study plan (Version) | Category of Branch/Specialization | Recommended semester |
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